spaCy/spacy/lang/mk/__init__.py
Adriane Boyd 724831b066 Merge remote-tracking branch 'upstream/master' into chore/update-develop-from-master
* Update Macedonian for v3
* Update Turkish for v3
2020-11-25 11:49:34 +01:00

49 lines
1.4 KiB
Python

from typing import Optional
from thinc.api import Model
from .lemmatizer import MacedonianLemmatizer
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .lex_attrs import LEX_ATTRS
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from ...language import Language
from ...attrs import LANG
from ...util import update_exc
from ...lookups import Lookups
class MacedonianDefaults(Language.Defaults):
lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
lex_attr_getters[LANG] = lambda text: "mk"
# Optional: replace flags with custom functions, e.g. like_num()
lex_attr_getters.update(LEX_ATTRS)
# Merge base exceptions and custom tokenizer exceptions
tokenizer_exceptions = update_exc(BASE_EXCEPTIONS, TOKENIZER_EXCEPTIONS)
stop_words = STOP_WORDS
@classmethod
def create_lemmatizer(cls, nlp=None, lookups=None):
if lookups is None:
lookups = Lookups()
return MacedonianLemmatizer(lookups)
class Macedonian(Language):
lang = "mk"
Defaults = MacedonianDefaults
@Macedonian.factory(
"lemmatizer",
assigns=["token.lemma"],
default_config={"model": None, "mode": "rule"},
default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(nlp: Language, model: Optional[Model], name: str, mode: str):
return MacedonianLemmatizer(nlp.vocab, model, name, mode=mode)
__all__ = ["Macedonian"]